ML Ops Analyst Intern

Internship On Site (Internship) @Eli Lilly and Company in Data Science
  • Bengaluru View on Map
  • Post Date : March 10, 2022
  • Apply Before : April 9, 2022

Job Description

ore Responsibilities:

As part of this team, we are looking for analysts who will use variety of data (including customer 360, market and product sales, prior channel activity and affinities etc) to maintain, update, assess and fine tune the performance of the underlying machine learning algorithms that drive personalized recommendations for all key brands for Lilly in the US.

  • Maintain stable and scalable solutions to extract data from diverse systems, cleanse and transform extremely large data sets into actionable business information
  • Writing and tuning complex SQL queries in a highly dynamic environment
  • Utilize knowledge of ML techniques (esp. Neural networks and Genetic Algorithms) to ensure that models are updated that models being used for the recommendation engine are to some extent “explainable”
  • Use knowledge of therapeutic area, market events, customer universe and available activity and affinity data, along with guidance from the Advanced Analytics and Data Science team (AADS) to implement alternate advanced analytical and statistical techniques as and when needed to test and validate models embedded in the personalization platform

Skills and expectations:

  • 0-2 hands-on experience with handling data with strong coding experience in R or Python
  • Creative problem solving, organization, attention to detail, flexibility and adaptability
  • Willingness to learn and deploy ML models; agility in learning to communicate complex analytics concisely
  • Demonstrated ability to meet deadlines while managing multiple large-scale projects in a fast-paced and rapidly changing environment
  • Ability to execute and innovate in a highly dynamic environment, including strong prioritization and attention to detail
  • Excellent communication (written & verbal) skills


  • Bachelor’s degree or master’s degree in technology, Statistics or Computer Science background

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